Enhancing the renewable energy payback period of a photovoltaic power generation system by water flow cooling

Sohani, Ali; Shahverdian, Mohammad Hassan; Sayyaadi, Hoseyn; Hoseinzadeh, Siamak; Memon, Saim

doi:10.37934/stve.3.1.7385

Cited by 11 publications

(4 citation statements)

References 49 publications

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“…Shakya S proposed a self-monitoring and analysis system for solar power plants using IoT and data mining algorithms [9]. Sohani A explored renewable energy recovery solutions for photovoltaic power plant systems through water flow cooling [10]. But their research lacks project management strategies.…”

Section: Related Workmentioning

confidence: 99%

Project Management Strategies in the Construction of Photovoltaic Power Plants

2024

ieim

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Photovoltaic power plant project management is a complex and difficult task that requires various aspects such as project management, technical research, equipment procurement, installation and commissioning. At the same time, China's photovoltaic power station projects also face problems such as poor construction environment, unstable equipment quality, and fast technological updates. This article combines the actual situation of photovoltaic power station project management and conducts in-depth research on how to apply project management to the construction of photovoltaic power station projects. With specific examples, it elaborates on the implementation effect of efficient management strategy in engineering construction. Meanwhile, this article can also optimize and improve existing debugging techniques, provide corresponding improvement measures, and evaluate their role in improving project efficiency and quality. The cost before the design phase experiment is 1.2 million yuan, and the cost after the experiment is 1.05 million yuan, with a cost reduction ratio of 0.143 yuan; the cost before the procurement phase experiment is 2.5 million yuan, and the cost after the experiment is 2.3 million yuan. The cost reduction ratio is 0.087. The research value of this article mainly lies in the empirical analysis and optimization of the project management system for photovoltaic power station engineering.

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Section: Related Workmentioning

confidence: 99%

Project Management Strategies in the Construction of Photovoltaic Power Plants

2024

ieim

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“…The performance of the PV system can be influenced by the climatic characteristics (insolation, ambient temperature, and wind speed). The values of the energy generated, final yield, PV system efficiency, performance ratio, and cell temperature losses can be correlated by the climatic characteristics of the particular location 17 . As BPV has the ability to absorb solar irradiance from both sides, Bhaduri and Kottantharayil 18 mounted BPV vertically and found out that there will be nearly zero soiling loss when BPV is positioned at 90° rather than at a latitude angle.…”

Section: Introductionmentioning

confidence: 99%

“…The values of the energy generated, final yield, PV system efficiency, performance ratio, and cell temperature losses can be correlated by the climatic characteristics of the particular location. 17 As BPV has the ability to absorb solar irradiance from both sides, Bhaduri and Kottantharayil 18 mounted BPV vertically and found out that there will be nearly zero soiling loss when BPV is positioned at 90°rather than at a latitude angle. When BPV is mounted vertically, it shows 15°C less temperature than at latitude angle.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic analysis of a bifacial PV/T‐driven ejector cooling and electrodialysis system for off‐grid sustainable climate refuge in hot‐arid climates

Niaz

Biçer

2023

Energy Science & Engineering

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In hot‐arid climatic regions like Qatar, it is important to facilitate pedestrians' journeys. One way to do so is by providing them with shelters, that is, from a station to their destination building. It is necessary for such shelters to provide on‐site space cooling and freshwater in an off‐grid condition. In this respect, the proposed off‐grid system in this study includes bifacial photovoltaic (BPV) and a solar thermal collector for energy generation with battery and thermal storage units. BPV with an efficiency of 16% can produce power up to about 6.1 kW on the rooftop, which also reduces the cooling load via effective shading. The ejector‐based cooling system is deployed for efficient space cooling in high ambient temperatures (more than 28°C), while for less than 28°C, both fan and water misting systems are operated for the comfort of pedestrians. Finally, an electrodialysis system is integrated to generate freshwater from seawater to be used for drinking and water misting purposes in the off‐grid sustainable shelter. The overall energy and exergy efficiencies of the system are calculated to be 13.2% and 5.29%, respectively. The effects of several parameters are also studied to observe the overall system efficiency and the energy generated and consumed by the system.

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“…The increasing population and modern lifestyle are threatening the traditional energy sources such as coal, oil, and natural gas. In order to meet the world's energy demand, renewable energy must be developed and utilized on a large scale (Wang H. et al, 2020;Sohani et al, 2021). In renewable energy, solar energy occupies a dominant position (Yuan et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Ultra-Short-Term Power Prediction of a Photovoltaic Power Station Based on the VMD-CEEMDAN-LSTM Model

Wang

Liu²,

Guan³

2022

Front. Energy Res.

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The prediction of photovoltaic power generation is helpful to the overall allocation of power planning departments and improves the utilization rate of photovoltaic power generation. Therefore, this study puts forward an ultra-short-term power forecasting model of a photovoltaic power station based on modal decomposition and deep learning. The methodology involved taking the data of a 50 MW photovoltaic power generation system in the Inner Mongolia Autonomous Region as a sample. Furthermore, the weather conditions were classified, and the historical power data were decomposed into multiple VMF subcomponents and residual terms by the VMD method. Then, the residual term was decomposed twice by the CEEMDAN method. All subcomponents were sent to the LSTM network for prediction, and the predicted value of the photovoltaic power station was obtained by superimposing the subcomponent prediction results. ARIMA, SVM, LSTM, and VMD-LSTM models were built to compare the accuracy with the proposed models. The results revealed that the prediction accuracy of a non-combination forecasting model was limited when the weather suddenly changed. The VMD method was used to decompose the residual term twice, which could fully extract the complex data information in the residual term, and when compared with the VMD-LSTM model, the eRMSE, eMAPE, and eTIC of the VMD-CEEMDAN-LSTM model were reduced by 0.104, 16.596, and 0.038, respectively. The second decomposition technology has obvious prediction advantages. The proposed quadratic modal decomposition model effectively improves the precision of ultra-short-term prediction of photovoltaic power plants.

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Enhancing the renewable energy payback period of a photovoltaic power generation system by water flow cooling

Cited by 11 publications

References 49 publications

Project Management Strategies in the Construction of Photovoltaic Power Plants

Project Management Strategies in the Construction of Photovoltaic Power Plants

Thermodynamic analysis of a bifacial PV/T‐driven ejector cooling and electrodialysis system for off‐grid sustainable climate refuge in hot‐arid climates

Ultra-Short-Term Power Prediction of a Photovoltaic Power Station Based on the VMD-CEEMDAN-LSTM Model

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